Technical Abstract:
Reports indicate that iron deficiency is the most prevalent micronutrient problem in the world. Increasing the amount of bioavailable micronutrients such as iron and zinc in plant foods for human consumption is a challenge, especially in developing countries where plant foods comprise a significant portion of the diet. Legume seeds have the potential to provide the essential nutrients required by humans. However, the concentrations of minerals such as Fe and Zn are low when compared to other foods. In order to increase the seed mineral concentration, it is important to understand the genetic basis for mineral concentration in the seeds and the rate limiting steps involved in the mineral distribution. To determine the loci influencing seed mineral concentrations in legumes, 100 lines of Medicago truncatula RIL population (Jemalong x DZA315.16) were grown for seed harvest for subsequent seed mineral analysis using the ICP-MS. PLABQTL software was used to identify quantitative trait loci (QTLs) linked to 71 previously mapped molecular markers using composite interval mapping. A LOD threshold of 4.20 was used to report a significant QTL. LOD score threshold was determined using the permutation test (1000 repetitions) at a p value of 0.05 for normally distributed data. Frequency distribution of seed Fe showed transgressive segregation in the RIL population. There was no correlation between Fe and other mineral concentrations. Significant Fe QTL was found on chromosome 7 with a high level of explained variance (30.7%). This QTL overlapped with a significant Zn QTL which also had had a high level of explained variance (21.2%). Additional lines of the same population and a new RIL population are being grown for QTL analysis. Near isogenic lines are being developed to fine map the loci of interest. New molecular markers are also currently being developed for these populations. Experiments are also being developed to analyze the whole plant partitioning of Fe in some of the exemplar RILs which will enable us to assess the possible genotype specific differences in total plant uptake and whole plant partitioning. This work was supported in part by funds from USDA-ARS under Agreement No. 58-6250-6-001 and from the Harvest Plus Project under Agreement No. 58-6250-4-F029 to MAG.